Spectrally resolved Raman lidar measurements of gaseous and liquid water in the atmosphere

Spectrally-Resolved Raman Lidar to Measure Atmospheric Three-Phase Water Simultaneously

We report on a spectrally-resolved Raman lidar that can simultaneously profile backscattered Raman spectrum signals from water vapor, water droplets and ice crystals as well as aerosol fluorescence in the atmosphere. The lidar emits a 354.8-nm ultraviolet laser radiation and samples echo signals in the 393.0-424.0 nm wavelength range with a 1.0-nm spectral resolution. A spectra decomposition method is developed to retrieve fluorescence spectra, water vapor Raman spectra and condensed (liquid and/or ice) water Raman spectra successively. Based on 8 different clear-sky nighttime measurement results, the entire atmospheric water vapor Raman spectra are for the first time obtained by lidar. The measured normalized water vapor Raman spectra are nearly invariant and can serve as background reference for atmospheric water phase state identification under various weather conditions. For an ice virga event, it’s found the extracted condensed water Raman spectra are highly similar in shape to theoretical ice water Raman spectra reported by Slusher and Derr (1975). In conclusion, the lidar provides an effective way to measure three-phase water simultaneously in the atmosphere and to study of cloud microphysics as well as interaction between aerosols and clouds.

Preliminary exploration of atmospheric water vapor, liquid water and ice water by ultraviolet Raman lidar

Water is the only atmospheric component with three phases. In this work, ultraviolet Raman lidar is developed for synchronous measurements of water vapor, liquid water and ice water in Xi'an (34.233°N, 108.911°E), China. Different interference filters are designed to construct individual water Raman channels, and the corresponding central wavelength and bandwidth are determined by 399.0 nm (3.1 nm), 403.0 nm (5.0 nm) and 407.6 nm (0.6 nm) in ice water, liquid water and water vapor Raman channels, respectively. The mutual interference effect originating from the overlapping characteristics of water Raman spectra is further analyzed, and an accurate retrieval method based on linear simultaneous equations and mutual interference degrees is proposed for synchronous three-phase water mixing ratio profiles. Preliminary measurements are carried out in the Centre for lidar remote sensing research of Xi'an University of Technology, and representative measurement examples are obtained and validated for the performance of the Raman lidar system. Synchronous mixing ratio profiles in water vapor, liquid water and ice water are retrieved, and the corresponding extinction coefficient and relative humidity profiles are also combined to reveal the variation characteristics in three-phase waters. The possible aerosol fluorescence are analyzed as well, and it is inferred that the aerosol fluorescence might affect (possibly overestimate) the derived mixing ratio values of the liquid water and ice water. The effective detection can reach up to a height of 5 km under cloudy weather, and synchronized growth in water vapor and liquid water content is obtained in cloud layers. Continuous observations are also made under hazy weather conditions, and the temporal and spatial evolution trends of three-phase waters in clouds are successfully realized. Preliminary exploration and results validate the feasibility of ultraviolet Raman lidar for synchronous measurements of atmospheric water vapor, liquid water and ice water.

Simultaneous wind and rainfall detection by power spectrum analysis using a VAD scanning coherent Doppler lidar

Doppler wind lidar is an effective tool for wind detection with high temporal and spatial resolution. However, precise wind profile measurement under rainy conditions is a challenge, due to the interfering signals from raindrop reflections. In this work, a compact all-fiber coherent Doppler lidar (CDL) at working wavelength of 1.5 µm is applied for simultaneous wind and precipitation detection. The performance of the lidar is validated by comparison with the weather balloons. Thanks to the ability of precise spectrum measurement, both aerosol and rainfall signals can be detected by the CDL under rainy conditions. The spectrum width is used to identify the precipitation events, during which the two-peak Doppler spectrum is observed. The spectrum is fitted by a two-component Gaussian model and two velocities are obtained. By using the velocity-azimuth display (VAD) scanning technique, wind speed and rainfall speed are simultaneously retrieved. The false detection probability of wind speed in the rainy conditions is thus reduced.

Concept for maritime near-surface surveillance using water Raman scattering

We discuss a maritime surveillance and detection concept based on Raman scattering of water molecules. Using a range-gated scanning lidar that detects Raman scattered photons from water, the absence or change of signal indicates the presence of a non-water object. With sufficient spatial resolution, a two-dimensional outline of the object can be generated by the scanning lidar. Because Raman scattering is an inelastic process with a relatively large wavelength shift for water, this concept avoids the often problematic elastic scattering for objects at or very close to the water surface or from the bottom surface for shallow waters. The maximum detection depth for this concept is limited by the attenuation of the excitation and return Raman light in water. If excitation in the UV is used, fluorescence can be used for discrimination between organic and non-organic objects. In this paper, we present a lidar model for this concept and discuss results of proof-of-concept measurements. Using published cross section values, the model and measurements are in reasonable agreement and show that a sufficient number of Raman photons can be generated for modest lidar parameters to make this concept useful for near-surface detection.

Lidar to determine the fractions of ice, liquid and water vapor in polar tropospheric clouds

A new Lidar combining Raman spectroscopy and linear polarization analysis is presented. This new instrument identifies the fraction of ice, liquid, and water vapor in low level polar tropospheric clouds and provides the polarimetric S and P state of the backscattering 532 nm Lidar signal. An overview of the research applications is given followed by a theoretical estimation of the Lidar returns. The instrument concept and optical characteristics are discussed. First Lidar profiles and instrument evaluations will be provided during the conference.

Lidar-measured atmospheric N₂ vibrational-rotational Raman spectra and consequent temperature retrieval

We have built a spectrally resolved Raman lidar to measure atmospheric N₂ Stokes vibrational-rotational Raman spectra. The lidar applies a double-grating polychromator with a reciprocal linear dispersion of ~0.12 nm mm(-1) for the wavelength separation and a 32-channel linear-array photomultiplier tube for sampling the spectral signals. The lidar can together measure the individual S- and O-branch line signals from J = 0 (2) through 14 (16). A comparison shows an excellent agreement between the lidar-measured and theoretically-calculated spectra. Based on the signal ratio of two individual lines (e.g., S-branch J = 6 and 12), the atmospheric temperature profiles are derived without requiring a calibration from another reference temperature. In terms of the envelope shape of an even-J section of the measured S-branch lines, we have also developed a new temperature retrieval approach without needing a calibration from reference temperature data. Both the approaches can give rise to reasonable temperature profiles comparable to that from local radiosonde.

Atmospheric temperature measurements at altitudes of 5-30 km with a double-grating-based pure rotational Raman lidar

A pure rotational Raman (PRR) lidar based on a second-harmonic generation Nd:YAG laser is built for measuring the atmospheric temperature at altitudes of 5-30 km. A double-grating polychromator is designed to extract the wanted PRR signals and suppress the elastically backscattered light. Measured examples present the overall lidar performance. For the 1-h integrated lidar temperature profiles, the 1σ statistical uncertainty is less than 0.5 K up to ∼17  km, while it does not exceed 2 K at altitudes of 17-26.3 km. Based on 38 nights of high-quality lidar temperature data, the temperature variability is studied. It is found that the variability differs between the nights with inversion layer and those without it. On the nights without inversion layer, the local hour-to-hour temperature variability was mostly less than 1 K at altitudes of 5-17 km. At altitudes of 17-23 km, it grew to 1.2-2.4 K. On the nights with inversion layer, in the middle and upper troposphere, the significant variability was found to occur only at the inversion-layer altitudes. At other tropospheric altitudes off the inversion layer, the variability was generally less than 1 K. The statistical results indicate that the temperature variability mostly was stronger in the presence of inversion layer than in its absence.